Embodiments herein generally relate to the use and manufacture of items, and more particularly, concerns a method, service, and computer program for identifying leading key performance indicators of the use and/or manufacture of any item, such as electrostatographic printers and copiers or reproduction machines. This method is useful beyond the printers, copiers, and reproduction machines. In fact, it is not surprising to find a leading indicator to a critical lagging indicator occurs in a completely different piece of machinery, department, or even region, as the machinery, department, region that helps define the lagging indicator. By way of example, in a print shop it would not be surprising to find that metrics in the sales department predict (i.e. lead) lagging key performance indicators in the printing, binding, and even shipping departments, and of any business or manufacturing process.
Key performance indicators (KPIs) signal the progress of organizational objectives [7] (note that references to publications are indicated by reference numbers herein, and a list of references appears at the end of this specification). Some key performance indicators such as the sales revenue, per unit manufacturing cost, machine utilization, customer satisfaction, customer churn, etc. are paid much attention for operational and business decision making. These are called Lagging indicators which have already happened and are of critical importance. Note that the embodiments discussed below are not limited to lagging indicators, but are applicable to any focal KPIs. In a traditional way, domain experts find what variables may cause or lead the variance of those lagging indicators using their domain knowledge. Such variables are called Leading Indicators. They are the indication and causal roots of focal lagging indicators, and are actionable for the future performance of those lagging indicators [2]. However, as business processes and manufacturing processes become more complex, relying only upon human judgment to find leading indicators of direct resource relocation and process modification is labor intensive and error-prone.